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Dysphonia has been described in patients affected by coronavirus disease 2019 (COVID-19). The aim of this study was to evaluate the prevalence of dysphonia, and its severity and extent, of voice fatigue and of dysphagia in non hospitalized patients affected by COVID-19 in Lombardy, the Italian region most hit by the first explosive outbreak of COVID-19 in Europe. Demographic and clinical data of 160 consecutive patients, with COVID-19 diagnosis confirmed by nasal swabs processed by reverse transcription polymerase chain reaction, were gathered by means of telephone interviews performed by physicians in charge of daily follow-up. General and specific symptoms concerning voice and swallowing impairment were investigated. Dysphonia grade and duration were graded on 4-point scales, while voice fatigue was graded on a 5-point scale. Dysphonia was reported by 70 (43.7%) patients and was positively associated with voice fatigue (P < 0.001), cough (P = 0.005), rhinitis (P = 0.01), and dyspnea (P = 0.06); it was mild and/or moderate in 69 patients, but its duration was > 2 weeks in 33/70 (47.1%) patients and >1 month in 11/70 (15.7%). Grade and duration of dysphonia were positively associated with cough and rhinitis (all P values < 0.01). Voice fatigue was reported by 43/160 patients (26.8%) and its severity was correlated with dysphonia (P < 0.0001), cough (P = 0.02), rhinitis (P = 0.02), dyspnea (P < 0.001), and loss of appetite (P = 0.01). Dysphagia was encountered in 27/160 patients (16.9%) and was associated with dysgeusia, cough, arthralgia, myalgia and loss of appetite but not with dysphonia. Dysphonia was a highly prevalent and long-lasting symptom in this series; it has been underestimated to date. Further studies might shed light on the pathophysiology of voice disorders in COVID-19 patients. [ABSTRACT FROM AUTHOR]

• Ensemble classifiers can distinguish voice features of paralytic and structural dysphonia. • Identification of relevant features of voice pathology with predictor importance. • Identification of structural dysphonia subtypes in female patients. • Pre- and post-treatment voice quality assessment through machine learning. • Explainability methods highlight relevant metrics for post-treatment voice tracking. The voice pathology identification task has recently gained great attention. However, several research questions remain open. This study proposes an explainable AI framework to address the implicit role of age in voice pathology recognition and to investigate vocal quality improvement after surgical treatment in organic voice disorders. The aim is also to define an optimal features subset through predictor importance analysis. A set of 287 patients diagnosed with benign lesions of vocal folds (BLVF) and unilateral vocal fold paralysis (UVFP) was enrolled. Classification experiments were performed for female (F) and male (M) groups: they aimed at distinguishing BLVF from UVFP in age-unbalanced (E1) and age-balanced (E2) datasets, differentiating BLVF subclasses (E3), and detecting pre- and post-treatment conditions (E4). The comparison between E1 and E2 suggests that age does not influence the classification performance. In E1, 76% (F) and 81% (M) accuracies were obtained. The best features concerned vocal fold dynamics and articulator positioning for F and M datasets. In E3, an accuracy of 60% was achieved, suggesting that larger datasets are required. In E4, the best models showed 76% (F) and 72% (M) accuracy, with a good sensitivity in detecting pre-treatment patients. The error rate analysis proved that UVFP was the most misclassified group. Moreover, an agreement between the AI outcome and perceptual evaluations was detected for misclassified recordings. These results suggest their clinical relevance to highlight key aspects of voice quality recovery and to define acoustic parameters that otolaryngologists could employ to monitor the patient's follow-up. [ABSTRACT FROM AUTHOR]

Summary Purpose Smartphone technology provides new opportunities for recording standardized voice samples of patients and transmitting the audio files to the voice laboratory. This drastically improves the achievement of baseline designs, used in research on efficiency of voice treatments. However, the basic requirement is the suitability of smartphones for recording and digitizing pathologic voices (mainly characterized by period perturbations and noise) without significant distortion. In a previous article, this was tested using realistic synthesized deviant voice samples (/a:/) with three precisely known levels of jitter and of noise in all combinations. High correlations were found between jitter and noise to harmonics ratio measured in (1) recordings via smartphones, (2) direct microphone recordings, and (3) sound files generated by the synthesizer. In the present work, similar experiments were performed (1) in the presence of increasing levels of ambient noise and (2) using synthetic deviant voice samples (/a:/) as well as synthetic voice material simulating a deviant short voiced utterance (/aiuaiuaiu/). Results Ambient noise levels up to 50 dB A are acceptable. However, signal processing occurs in some smartphones, and this significantly affects estimates of jitter and noise to harmonics ratio when formant changes are introduced in analogy with running speech. The conclusion is that voice material must provisionally be limited to a sustained /a/. [ABSTRACT FROM AUTHOR]

Abstract: Vocal folds oscillation crucially influences all the basic qualities of voice, such as pitch and loudness, as well as the spectrum. Stroboscopy provides the standard view of the larynx. However, a two-dimensional high-speed imaging system currently cannot provide enough image resolution to evaluate irregular vocal fold vibrations, due to the limitation of transmission speed and storage volume. Videokymography is a new diagnostic tool developed to overcome specific limitations of stroboscopy in severely dysphonic patients with an aperiodic signal. It registers the movements of the vocal folds with a high time resolution on a line perpendicular to the glottis. The technique, being independent from the periodicity and intensity of the vocal signal, allows an objective evaluation of vocal folds function. However, due to its novelty, no established clinical evaluation protocol, or validity and reliability data are available for videokymography. Moreover, few results concerning objective parameter estimation from videokymographic images are available. The main focus of this paper is on measuring and tracking quantitative parameters for objective vocal fold functional assessment, from videokymographic (VKG) examinations of subjects with normal and pathological laryngeal function, based on active contour search implemented with a properly adjusted robust snake algorithm. The method is designed to deliver to the clinician the essential objective information of VKG in an effective way, as an aid to its subjective and intuitive skilfulness. A set of VKG images has been analysed, coming both from healthy and dysphonic subjects, recorded at the Otolaryngology Department, University of Milan, Italy, showing the robustness and reliability of the proposed technique. [Copyright &y& Elsevier]

Summary Smartphone technology provides new opportunities for recording standardized voice samples of patients and sending the files by e-mail to the voice laboratory. This drastically improves the collection of baseline data, as used in research on efficiency of voice treatments. However, the basic requirement is the suitability of smartphones for recording and digitizing pathologic voices (mainly characterized by period perturbations and noise) without significant distortion. In this experiment, two smartphones (a very inexpensive one and a high-level one) were tested and compared with direct microphone recordings in a soundproof room. The voice stimuli consisted in synthesized deviant voice samples (median of fundamental frequency: 120 and 200 Hz) with three levels of jitter and three levels of added noise. All voice samples were analyzed using PRAAT software. The results show high correlations between jitter, shimmer, and noise-to-harmonics ratio measured on the recordings via both smartphones, the microphone, and measured directly on the sound files from the synthesizer. Smartphones thus appear adequate for reliable recording and digitizing of pathologic voices. [ABSTRACT FROM AUTHOR]

Summary: Objective: Time consuming is an important aspect in assessing dysphonic patients. So, the English version of the Voice Handicap Index (VHI-30), a self-administered questionnaire consisting of 30 items used to evaluate patients' self-perception of voice problems, was reduced to 10 items (VHI-10) for clinical purposes. In 2010, an Italian version of VHI-30 was validated, now the aims of this study were to analyze the psychometric properties of an Italian version of VHI-10 and to evaluate its validity in a cohort of patients affected by organic or functional dysphonia. Study Design: Cross-sectional study. Methods: The Italian version of the VHI-30 was submitted to 372 dysphonic participants and 120 healthy control subjects and was conducted again 2 weeks later. The 10 items constituting the VHI-10 were extracted from the VHI-30. For 73 dysphonic patients, the questionnaire was also administered after treatment. Results: The scores of the control group were significantly lower with respect to all diagnostic subgroups (P <0.001). The Cronbach's α, test-retest, and Pearson's correlation index demonstrated high reliability and validity of the Italian VHI-10. The ratio of the VHI-10 and VHI-30 scores was higher than 0.333 in all subgroups. Conclusion: This study demonstrated that the Italian VHI-10 is a robust tool that can adequately represent and replace the VHI-30. The reported results support the use of the VHI-10 for the Italian population in clinical settings owing to its validity and rapid and simple use. [Copyright &y& Elsevier]